Question

Variable Name Explanation Options Cars Number of motor vehicles in your household Income Your income in Dollars ($). Support Belief that Australia should financially support developing {Yes, No} countries in their efforts to address Climate Change Cause Who/what you think is most responsible for Climate Change {Mostly Human, Mostly Natural, There is no Climate Change, Unsure/Undecided} Solar_Panals Willingness to Install Solar Panels {Already Installed, Plan to Install, Would Install if I could, No plan to install/Do not want} Nominal variable: ……………………………………………………. Ordinal variable: ………………………………………………………. Discrete variable: ……………………………………………………… Continuous variable: ……………………………………………….. Dummy variable: ………………………………………………………

Answer 1

Nominal variable: Cars, Support; Ordinal variable: Income, Cause; Discrete variable: Cars, Solar_Panels; Continuous variable: Income; Dummy variable: Nominal variable: Support.

Expalanation:

Certainly, let's break down the analysis step by step:

Identify Variable Types:

Nominal variable: Cars, Support

Ordinal variable: Income, Cause

Discrete variable: Cars, Solar_Panels

Continuous variable: Income

Dummy variable: Support

Nominal Variables:

"Cars" represents the number of motor vehicles, and "Support" represents the belief about Australia's financial support for developing countries in climate change efforts. These variables have categories without any inherent order.

Ordinal Variables:

"Income" is measured in dollars and has a meaningful order, but the intervals between income categories may not be uniform.

"Cause" represents the perception of responsibility for climate change, with categories having a meaningful order from "Mostly Human" to "Unsure/Undecided."

Discrete Variables:

"Cars" takes distinct, separate values representing the count of motor vehicles.

"Solar_Panels" represents the willingness to install solar panels and has distinct categories.

Continuous Variable:

"Income" is a continuous variable as it can take any real number within a given range.

Dummy Variable:

"Support" can be considered a dummy variable, taking binary values ("Yes" or "No") to indicate whether there is a belief in Australia's financial support for developing countries in addressing climate change.

By systematically categorizing each variable based on its characteristics and purpose, this analysis provides a clear understanding of the nature of each variable in the given context. Such categorization is fundamental in statistical analysis and aids in selecting appropriate methods for data interpretation and modeling.